TGFB1 T10C and XRCC1 G399A SNPs were associated with CC risk in univariate and multivariate analysis and displayed allele-dosage effects and coselection in cancer patients. Patients harboring the majority allele TGFB1 T10 (Leu) or the variant allele XRCC1 399A (Gln) have approximately 1.5-fold increased risk to develop CC. Host SNPs genotyping may provide relevant biomarkers for CC risk assessment in personalized preventive medicine.

In cases of nuclear and radiological accidents, public health and emergency response need to assess the magnitude of radiation exposure regardless of whether they arise from disaster, negligence, or deliberate act. Here we report the establishment of a national reference dose–response calibration curve (DRCC) for dicentric chromosome (DC), prerequisite to assess radiation doses received in accidental exposures. Peripheral blood samples were collected from 10 volunteers (aged 20–40 years, median = 29 years) of both sexes (three females and seven males). Blood samples, cytogenetic preparation, and analysis followed the International Atomic Energy Agency EPR-Biodosimetry 2011 report. Irradiations were performed using 320 kVp X-rays. Metafer system was used for automated and assisted (elimination of false-positives and inclusion of true-positives) metaphases findings and DC scoring. DC yields were fit to a linear–quadratic model. Results of the assisted DRCC showed some variations among individuals that were not statistically significant (homogeneity test, P = 0.66). There was no effect of age or sex (P > 0.05). To obtain representative national DRCC, data of all volunteers were pooled together and analyzed. The fitted parameters of the radiation-induced DC curve were as follows: Y = 0.0020 (±0.0002) + 0.0369 (±0.0019) *D + 0.0689 (±0.0009) *D2. The high significance of the fitted coefficients (z-test, P < 0.0001), along with the close to 1.0 p-value of the Poisson-based goodness of fit (χ2 = 3.51, degrees of freedom = 7, P = 0.83), indicated excellent fitting with no trend toward lack of fit. The curve was in the middle range of DRCCs published in other populations. The automated DRCC over and under estimated DCs at low (<1 Gy) and high (>2 Gy) doses, respectively, with a significant lack of goodness of fit (P < 0.0001). In conclusion, we have established the reference DRCC for DCs induced by 320 kVp X-rays. There was no effect of age or sex in this cohort of 10 young adults. Although the calibration curve obtained by the automated (unsupervised) scoring misrepresented dicentric yields at low and high doses, it can potentially be useful for triage mode to segregate between false-positive and near 2-Gy exposures from seriously irradiated individuals who require hospitalization.

BACKGROUNDCervical cancer is a predominantly human papillomavirus (HPV)‐driven disease worldwide. However, its incidence is unexplainably low in western Asia, including Saudi Arabia. Using this paradigm, we investigated the role of HPV infection rate and host genetic predisposition in TP53 G72C single nucleotide polymorphism (SNP) presumed to affect cancer incidence.METHODSPatients treated between 1990 and 2012 were reviewed, and a series of 232 invasive cervical cancer cases were studied and compared with 313 matched controls without cancer. SNP was genotyped by way of direct sequencing. HPV linear array analysis was used to detect and genotype HPV in tumor samples.RESULTSThe incidence of cervical cancer revealed bimodal peaks at 42.5 years, with a slighter rebound at 60.8 years. Among all cases, 77% were HPV‐positive and 16 HPV genotypes were detected—mostly genotypes 16 (75%) and 18 (9%)—with no difference by age, histology, or geographical region. Although the TP53 G72C genotype was not associated with overall cervical cancer risk, it was significantly associated with HPV positivity (odds ratio, 0.57; 95% confidence interval, 0.36‐0.90; P = .016). Furthermore, the variant C allele was significantly overtransmitted in the population (P < .0003).CONCLUSIONCervical cancer incidence displays bimodal curve peaking at a young age with secondary rebound at older age. The combination of relative low HPV infection and variant TP53 72C allele overtransmission provide a plausible explanation for the low incidence of cervical cancer in our population. Therefore, HPV screening and host SNP genotyping may provide more relevant biomarkers to gauge the risk of developing cervical cancer. Cancer 2017;123:2459–66. © 2017 The Authors. Cancer published by Wiley Periodicals, Inc. on behalf of American Cancer Society. This is an open access article under the terms of the Creative Commons Attribution NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

Wearing face masks have been implemented as a public and personal health control measure against the spread of coronavirus disease (COVID-19). However, the protection level of nonmedical face masks, such as women face veils, is still uncertain. This study aimed to assess the filtration efficiency (FE; percentage of particles retained by a mask) of different types of medical masks (either as sealed or unsealed, single or doubled), non-medical masks (cloth masks) and face veils. FE of face masks was evaluated using an in-house 3D-printed air duct connected to the Aerotrak particle counter with a capability of counting particle sizes of 0.3, 0.5, 0.7, 1, 2 and 5 μm. A set of 10 earloop surgical masks,10 tie-on surgical masks, 3 triple-layers reusable cloth masks and 3 types (short, medium and long) of traditional face veils were included in the study. The unsealed surgical masks showed intermediate FE (36.54-80.58%), with no observed differences between tie-on and earloop or single and doubled masks. For each mask type, the mean FE values of sealed surgical masks (FE≥99.16%) was significantly higher (P<0.001) than the unsealed ones (FE≤80.58%). No significant difference was observed in the mean FE values between unsealed surgical masks and either cloth masks (FE=23.19-75.35%, P=0.26) or face veils (FE=19.10- 70.68%, P=0.14). However, a mockup experiment showed that wearing a surgical mask under the face veil significantly improve the FE (33.73-79.18%; P<0.001). We conclude that besides sealed surgical masks that ensure optimal filtration under the experimental conditions, the unsealed surgical and cloth masks and face veils showed comparable performance and acceptable protection at 5 μm particle size, which is the most relevant particle size associated with COVID-19 infectious droplets. Wearing a surgical mask under the face veil significantly improves the FE compared to wearing a face veil alone.